Abstract: Feature selection has recently been the subject of intensive research in data mining, specially for datasets with a large number of attributes. Recent work has shown that feature selection can have a positive effect on the performance of machine learning algorithms. The success of many learning algorithms in their attempts to construct models of data, hinges on the reliable identification of a small set of highly predictive attributes. The inclusion of irrelevant, redundant and noisy attributes in the model building process phase can result in poor predictive performance and increased computation. In this paper, a novel feature search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.
Abstract: Text Mining is around applying knowledge discovery
techniques to unstructured text is termed knowledge discovery in text
(KDT), or Text data mining or Text Mining. In decision tree
approach is most useful in classification problem. With this
technique, tree is constructed to model the classification process.
There are two basic steps in the technique: building the tree and
applying the tree to the database. This paper describes a proposed
C5.0 classifier that performs rulesets, cross validation and boosting
for original C5.0 in order to reduce the optimization of error ratio.
The feasibility and the benefits of the proposed approach are
demonstrated by means of medial data set like hypothyroid. It is
shown that, the performance of a classifier on the training cases from
which it was constructed gives a poor estimate by sampling or using a
separate test file, either way, the classifier is evaluated on cases that
were not used to build and evaluate the classifier are both are large. If
the cases in hypothyroid.data and hypothyroid.test were to be
shuffled and divided into a new 2772 case training set and a 1000
case test set, C5.0 might construct a different classifier with a lower
or higher error rate on the test cases. An important feature of see5 is
its ability to classifiers called rulesets. The ruleset has an error rate
0.5 % on the test cases. The standard errors of the means provide an
estimate of the variability of results. One way to get a more reliable
estimate of predictive is by f-fold –cross- validation. The error rate of
a classifier produced from all the cases is estimated as the ratio of the
total number of errors on the hold-out cases to the total number of
cases. The Boost option with x trials instructs See5 to construct up to
x classifiers in this manner. Trials over numerous datasets, large and
small, show that on average 10-classifier boosting reduces the error
rate for test cases by about 25%.
Abstract: E-services have significantly changed the way of
doing business in recent years. We can, however, observe poor use of
these services. There is a large gap between supply and actual eservices
usage. This is why we started a project to provide an
environment that will encourage the use of e-services. We believe
that only providing e-service does not automatically mean consumers
would use them. This paper shows the origins of our project and its
current position. We discuss the decision of using semantic web
technologies and their potential to improve e-services usage. We also
present current knowledge base and its real-world classification. In the paper, we discuss further work to be done in the project. Current
state of the project is promising.
Abstract: Intrusion Detection System is significant in network
security. It detects and identifies intrusion behavior or intrusion
attempts in a computer system by monitoring and analyzing the
network packets in real time. In the recent year, intelligent algorithms
applied in the intrusion detection system (IDS) have been an
increasing concern with the rapid growth of the network security.
IDS data deals with a huge amount of data which contains irrelevant
and redundant features causing slow training and testing process,
higher resource consumption as well as poor detection rate. Since the
amount of audit data that an IDS needs to examine is very large even
for a small network, classification by hand is impossible. Hence, the
primary objective of this review is to review the techniques prior to
classification process suit to IDS data.
Abstract: In order to guarantee secure communication for wireless sensor networks (WSNs), many user authentication schemes have successfully drawn researchers- attention and been studied widely. In 2012, He et al. proposed a robust biometric-based user authentication scheme for WSNs. However, this paper demonstrates that He et al.-s scheme has some drawbacks: poor reparability problem, user impersonation attack, and sensor node impersonate attack.
Abstract: In the effort to reduce water consumption for resorts,
more water conservation practices need to be implemented. Hence
water audits need to be performed to obtain a baseline of water
consumption, before planning water conservation practices. In this
study, a water audit framework specifically for resorts was created,
and the audit was performed on two resorts: Resort A in Langkawi,
Malaysia; and Resort B in Miri, Malaysia. From the audit, the total
daily water consumption for Resorts A and B were estimated to be
180m3 and 330 m3 respectively, while the actual water consumption
(based on water meter readings) were 175 m3 and 325 m3. This
suggests that the audit framework is reasonably accurate and may be
used to account for most of the water consumption sources in a
resort. The daily water consumption per guest is about 500 litres. The
water consumption of both resorts is poorly rated compared with
established benchmarks. Water conservation measures were
suggested for both resorts.
Abstract: Titanium alloys like Ti-6Al-2Sn-4Zr-6Mo (Ti-
6246) are widely used in aerospace applications. Component
manufacturing, however, is difficult and expensive as their
machinability is extremely poor. A thorough understanding of the
chip formation process is needed to improve related metal cutting
operations.In the current study, orthogonal cutting experiments have
been performed and theresulting chips were analyzed by optical
microscopy and scanning electron microscopy.Chips from aTi-
6246ingot were produced at different cutting speeds and cutting
depths. During the experiments, depending of the cutting conditions,
continuous or segmented chips were formed. Narrow, highly
deformed and grain oriented zones, the so-called shear zone,
separated individual segments. Different material properties have
been measured in the shear zones and the segments.
Abstract: Public bus service plays a significant role in our
society as people movers and to facilitate travels within towns and districts. The quality of service of public bus is always being
regarded as poor, or rather, underestimated as second class means of transportation. Reliability of service, or the ability to deliver service as planned, is one key element in perceiving the quality of bus service and the punctuality index is one of the performance parameters in determining the service reliability. This study
concentrates on evaluating the reliability performance of bus operation using punctuality index assessment. A week data for each
of six city bus routes is recorded using the on-board methodology to calculate the punctuality index for city bus service in Kota Bharu. The results revealed that the punctuality index for the whole city bus network is 94.25% (LOS B).
Abstract: Defense and Aerospace environment is continuously
striving to keep up with increasingly sophisticated Information
Technology (IT) in order to remain effective in today-s dynamic and
unpredictable threat environment. This makes IT one of the largest
and fastest growing expenses of Defense. Hundreds of millions of
dollars spent a year on IT projects. But, too many of those millions
are wasted on costly mistakes. Systems that do not work properly,
new components that are not compatible with old ones, trendy new
applications that do not really satisfy defense needs or lost through
poorly managed contracts.
This paper investigates and compiles the effective strategies that
aim to end exasperation with low returns and high cost of
Information Technology acquisition for defense; it tries to show how
to maximize value while reducing time and expenditure.
Abstract: This paper presents the modeling and simulation of a hybrid proton exchange membrane fuel cell (PEMFC) with an energy storage system for use in a stand-alone distributed generation (DG) system. The simulation model consists of fuel cell DG, lead-acid battery, maximum power point tracking and power conditioning unit which is modeled in the MATLAB/Simulink platform. Poor loadfollowing characteristics and slow response to rapid load changes are some of the weaknesses of PEMFC because of the gas processing reaction and the fuel cell dynamics. To address the load-tracking issues in PEMFC, a hybrid PEMFC and battery storage system is considered and modelled. The model utilizes PEMFC as the main energy source whereas the battery functions as energy storage to compensate for the limitations of PEMFC.Simulation results are given to show the overall system performance under light and heavyloading conditions.
Abstract: Although lighting systems powered by Photovoltaic
(PV) cells have existed for many years, they are not widely used,
especially in lighting for buildings, due to their high initial cost and
low conversion efficiency. One of the technical challenges facing PV
powered lighting systems has been how to use dc power generated by
the PV module to energize common light sources that are designed to
operate efficiently under ac power. Usually, the efficiency of the dc
light sources is very poor compared to ac light sources. Rapid
developments in LED lighting systems have made this technology a
potential candidate for PV powered lighting systems. This study
analyzed the efficiency of each component of PV powered lighting
systems to identify optimum system configurations for different
applications.
Abstract: This paper introduces our first efforts of developing a
new team for RoboCup Middle Size Competition. In our robots we
have applied omni directional based mobile system with omnidirectional
vision system and fuzzy control algorithm to navigate
robots. The control architecture of MRL middle-size robots is a three
layered architecture, Planning, Sequencing, and Executing. It also
uses Blackboard system to achieve coordination among agents.
Moreover, the architecture should have minimum dependency on low
level structure and have a uniform protocol to interact with real
robot.
Abstract: Thyroid dysfunction is one of the most frequently
reported complications of chronic blood transfusion therapy in patients with beta-thalassemia major (BTM). However, the occurrence of thyroid dysfunction and its possible association with
iron overload in BTM patients is still under debate. Therefore, this
study aimed to investigate the status of thyroid functions and iron overload in adolescent and young adult patients with BTM in Jordan population. Thirty six BTM patients aged 12-28 years and matched controls were included in this study. All patients have been receiving frequent blood transfusion to maintain pretransfusion hemoglobin
concentration above 10 g dl-1 and deferoxamine at a dose of 45 mg kg-1 day-1 (8 h, 5-7 days/week) by subcutaneous infusion. Blood
samples were drawn from patients and controls. The status of thyroid functions and iron overload was evaluated by measurements of serum
free thyroxine (FT4), triiodothyronine (FT3), thyrotropin (TSH) and
serum ferritin level. A number of some hematological and
biochemical parameters were also measured. It was found that hematocrit, serum ferritin, hemoglobin, FT3 and zinc, copper mean values were significantly higher in the patients than in the controls (P< 0.05). On other hand, leukocyte, FT4 and TSH mean values were
similar to that of the controls. In addition, our data also indicated that
all of the above examined parameters were not significantly affected
by the patient-s age and gender. Deferoxamine approach for removing excess iron from our BTM patient did not normalize the
values of serum ferritin, copper and zinc, suggesting poor compliance
with deferoxamine chelation therapy. Thus, we recommend the use
of a combination of deferoxamine and deferiprone to reduce the risk
of excess of iron in our patients. Furthermore, thyroid dysfunction
appears to be a rare complication, because our patients showed
normal mean levels for serum TSH and FT4. However, high mean
levels of serum ferritin, zinc, copper might be seen as potential risk
factors for initiation and development of thyroid dysfunctions and
other diseases. Therefore, further studies must be carried out at
yearly intervals with large sample number, to detect subclinical
thyroid dysfunction cases.
Abstract: The performance of sensor-less controlled induction
motor drive depends on the accuracy of the estimated speed.
Conventional estimation techniques being mathematically complex
require more execution time resulting in poor dynamic response. The
nonlinear mapping capability and powerful learning algorithms of
neural network provides a promising alternative for on-line speed
estimation. The on-line speed estimator requires the NN model to be
accurate, simpler in design, structurally compact and computationally
less complex to ensure faster execution and effective control in real
time implementation. This in turn to a large extent depends on the
type of Neural Architecture. This paper investigates three types of
neural architectures for on-line speed estimation and their
performance is compared in terms of accuracy, structural
compactness, computational complexity and execution time. The
suitable neural architecture for on-line speed estimation is identified
and the promising results obtained are presented.
Abstract: The abnormal increase in the number of applications available for download in Android markets is a good indication that they are being reused. However, little is known about their real reusability potential. A considerable amount of these applications is reported as having a poor quality or being malicious. Hence, in this paper, an approach to measure the reusability potential of classes in Android applications is proposed. The approach is not meant specifically for this particular type of applications. Rather, it is intended for Object-Oriented (OO) software systems in general and aims also to provide means to discard the classes of low quality and defect prone applications from being reused directly through inheritance and instantiation. An empirical investigation is conducted to measure and rank the reusability potential of the classes of randomly selected Android applications. The results obtained are thoroughly analyzed in order to understand the extent of this potential and the factors influencing it.
Abstract: Learning programming is difficult for many learners. Some researches have found that the main difficulty relates to cognitive load. Cognitive overload happens in programming due to the nature of the subject which is intrinisicly over-bearing on the working memory. It happens due to the complexity of the subject itself. The problem is made worse by the poor instructional design methodology used in the teaching and learning process. Various efforts have been proposed to reduce the cognitive load, e.g. visualization softwares, part-program method etc. Use of many computer based systems have also been tried to tackle the problem. However, little success has been made to alleviate the problem. More has to be done to overcome this hurdle. This research attempts at understanding how cognitive load can be managed so as to reduce the problem of overloading. We propose a mechanism to measure the cognitive load during pre instruction, post instruction and in instructional stages of learning. This mechanism is used to help the instruction. As the load changes the instruction is made to adapt itself to ensure cognitive viability. This mechanism could be incorporated as a sub domain in the student model of various computer based instructional systems to facilitate the learning of programming.
Abstract: In this paper, we propose an effective relay
communication for layered video transmission as an alternative to
make the most of limited resources in a wireless communication
network where loss often occurs. Relaying brings stable multimedia
services to end clients, compared to multiple description coding
(MDC). Also, retransmission of only parity data about one or more
video layer using channel coder to the end client of the relay device is
paramount to the robustness of the loss situation. Using these
methods in resource-constrained environments, such as real-time user
created content (UCC) with layered video transmission, can provide
high-quality services even in a poor communication environment.
Minimal services are also possible. The mathematical analysis shows
that the proposed method reduced the probability of GOP loss rate
compared to MDC and raptor code without relay. The GOP loss rate
is about zero, while MDC and raptor code without relay have a GOP
loss rate of 36% and 70% in case of 10% frame loss rate.
Abstract: With the global financial crisis turning into what more
and more appears to be a prolonged “Great Recession", we are
witnessing marked reductions in remittance transfers to developing
countries with the likely possibility that overall flows will decline
even further in the near future. With countless families reliant on
remittance inflows as a source of income maintaining their economic
livelihood, a reduction would put many at risk of falling below or
deeper into poverty. Recognizing the importance of remittance
inflows as a lifeline to the poor, policy should aim to (1) reduce the
barriers to remit in both sending and receiving nations thus easing the
decline in transfers; (2) leverage the development impacts of
remittances; and (3) buffer vulnerable groups dependent on
remittance transfers as a source of livelihood through sound countercyclical
macroeconomic policies.
Abstract: Image registration plays an important role in the
diagnosis of dental pathologies such as dental caries, alveolar bone
loss and periapical lesions etc. This paper presents a new wavelet
based algorithm for registering noisy and poor contrast dental x-rays.
Proposed algorithm has two stages. First stage is a preprocessing
stage, removes the noise from the x-ray images. Gaussian filter has
been used. Second stage is a geometric transformation stage.
Proposed work uses two levels of affine transformation. Wavelet
coefficients are correlated instead of gray values. Algorithm has been
applied on number of pre and post RCT (Root canal treatment)
periapical radiographs. Root Mean Square Error (RMSE) and
Correlation coefficients (CC) are used for quantitative evaluation.
Proposed technique outperforms conventional Multiresolution
strategy based image registration technique and manual registration
technique.
Abstract: This paper presents a computational study of the separated flow in a planer asymmetric diffuser. The steady RANS equations for turbulent incompressible fluid flow and six turbulence closures are used in the present study. The commercial software code, FLUENT 6.3.26, was used for solving the set of governing equations using various turbulence models. Five of the used turbulence models are available directly in the code while the v2-f turbulence model was implemented via User Defined Scalars (UDS) and User Defined Functions (UDF). A series of computational analysis is performed to assess the performance of turbulence models at different grid density. The results show that the standard k-ω, SST k-ω and v2-f models clearly performed better than other models when an adverse pressure gradient was present. The RSM model shows an acceptable agreement with the velocity and turbulent kinetic energy profiles but it failed to predict the location of separation and attachment points. The standard k-ε and the low-Re k- ε delivered very poor results.